PMID- 36684250
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20230201
IS  - 2296-875X (Print)
IS  - 2296-875X (Electronic)
IS  - 2296-875X (Linking)
VI  - 9
DP  - 2022
TI  - Identifying an optimal machine learning model generated circulating biomarker to 
      predict chronic postoperative pain in patients undergoing hepatectomy.
PG  - 1068321
LID - 10.3389/fsurg.2022.1068321 [doi]
LID - 1068321
AB  - Chronic postsurgical pain (CPSP) after hepatectomy is highly prevalent and 
      challenging to treat. Several risk factors have been unmasked for CPSP after 
      hepatectomy, such as acute postoperative pain. The current secondary analysis of 
      a clinical study sought to extend previous research by investigating more 
      clinical variables and inflammatory biomarkers as risk factors for CPSP after 
      hepatectomy and sifting those strongly related to CPSP to build a reliable 
      machine learning model to predict CPSP occurring. Participants included 91 adults 
      undergoing hepatectomy who was followed 3 months postoperatively. Twenty-four 
      hours after surgery, participants completed numerical rating scale (NRS) grading 
      and blood sample collecting. Three months after surgery, participants also 
      reported whether CPSP occurred through follow-up. The Random Forest and Support 
      Vector Machine models were conducted to predict pain outcomes 3 months after 
      surgery. The results showed that the SVM model had better performance in 
      predicting CPSP which consists of acute postoperative pain (evaluated by NRS) and 
      matrix metalloprotease 3 (MMP3) level. What's more, besides traditional 
      cytokines, several novel inflammatory biomarkers like C-X-C motif chemokine 
      ligand 10 (CXCL10) and MMP2 levels were found to be closely related to CPSP and a 
      novel spectrum of inflammatory biomarkers was created. These findings demonstrate 
      that the SVM model consisting of acute postoperative pain and MMP3 level predicts 
      greater chronic pain intensity 3 months after hepatectomy and with this model, 
      intervention administration before CPSP occurs may prevent or minimize CPSP 
      intensity successfully.
CI  - (c) 2023 Hong, Li, Ye, Yan, Yang and Jiang.
FAU - Hong, Ying
AU  - Hong Y
AD  - Department of Anesthesiology, West China Hospital, Sichuan University and The 
      Research Units of West China (2018RU012), Chinese Academy of Medical Sciences, 
      Chengdu, China.
AD  - Laboratory of Anesthesia and Critical Care Medicine, Department of 
      Anesthesiology, Translational Neuroscience Center, West China Hospital, Sichuan 
      University, Chengdu, China.
FAU - Li, Yue
AU  - Li Y
AD  - Department of Anesthesiology, West China Hospital, Sichuan University and The 
      Research Units of West China (2018RU012), Chinese Academy of Medical Sciences, 
      Chengdu, China.
AD  - Laboratory of Anesthesia and Critical Care Medicine, Department of 
      Anesthesiology, Translational Neuroscience Center, West China Hospital, Sichuan 
      University, Chengdu, China.
FAU - Ye, Mao
AU  - Ye M
AD  - Department of Anesthesiology, West China Hospital, Sichuan University and The 
      Research Units of West China (2018RU012), Chinese Academy of Medical Sciences, 
      Chengdu, China.
AD  - Laboratory of Anesthesia and Critical Care Medicine, Department of 
      Anesthesiology, Translational Neuroscience Center, West China Hospital, Sichuan 
      University, Chengdu, China.
FAU - Yan, Siyu
AU  - Yan S
AD  - Department of Anesthesiology, West China Hospital, Sichuan University and The 
      Research Units of West China (2018RU012), Chinese Academy of Medical Sciences, 
      Chengdu, China.
AD  - Laboratory of Anesthesia and Critical Care Medicine, Department of 
      Anesthesiology, Translational Neuroscience Center, West China Hospital, Sichuan 
      University, Chengdu, China.
FAU - Yang, Wei
AU  - Yang W
AD  - Department of Anesthesiology, West China Hospital, Sichuan University and The 
      Research Units of West China (2018RU012), Chinese Academy of Medical Sciences, 
      Chengdu, China.
AD  - Laboratory of Anesthesia and Critical Care Medicine, Department of 
      Anesthesiology, Translational Neuroscience Center, West China Hospital, Sichuan 
      University, Chengdu, China.
FAU - Jiang, Chunling
AU  - Jiang C
AD  - Department of Anesthesiology, West China Hospital, Sichuan University and The 
      Research Units of West China (2018RU012), Chinese Academy of Medical Sciences, 
      Chengdu, China.
AD  - Laboratory of Anesthesia and Critical Care Medicine, Department of 
      Anesthesiology, Translational Neuroscience Center, West China Hospital, Sichuan 
      University, Chengdu, China.
LA  - eng
PT  - Journal Article
DEP - 20230106
PL  - Switzerland
TA  - Front Surg
JT  - Frontiers in surgery
JID - 101645127
PMC - PMC9852489
OTO - NOTNLM
OT  - SVM
OT  - chronic pain
OT  - machine learning (ML)
OT  - post-hepatectomy
OT  - prediction model
COIS- The authors declare that the research was conducted in the absence of any 
      commercial or financial relationships that could be construed as a potential 
      conflict of interest.
EDAT- 2023/01/24 06:00
MHDA- 2023/01/24 06:01
PMCR- 2023/01/06
CRDT- 2023/01/23 04:21
PHST- 2022/10/12 00:00 [received]
PHST- 2022/11/09 00:00 [accepted]
PHST- 2023/01/23 04:21 [entrez]
PHST- 2023/01/24 06:00 [pubmed]
PHST- 2023/01/24 06:01 [medline]
PHST- 2023/01/06 00:00 [pmc-release]
AID - 10.3389/fsurg.2022.1068321 [doi]
PST - epublish
SO  - Front Surg. 2023 Jan 6;9:1068321. doi: 10.3389/fsurg.2022.1068321. eCollection 
      2022.